{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Population Based Augmentation\n",
    "\n",
    "Run all cells below to visualize augmentations on a sample image.\n",
    "\n",
    "0, 1, or 2 augmentations will be applied.\n",
    "\n",
    "Does not include additional horizontal flip, pad/crop, or Cutout that may be applied beforehand during training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import PIL\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import pba.augmentation_transforms_hp as augmentation_transforms_hp\n",
    "from pba.utils import parse_log_schedule\n",
    "from pba.data_utils import parse_policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:final len 200\n",
      "INFO:tensorflow:final len 160\n"
     ]
    }
   ],
   "source": [
    "# Initialize CIFAR & SVHN policies.\n",
    "cifar_policy = (parse_log_schedule('schedules/rcifar10_16_wrn.txt', 200), 'cifar10_4000')\n",
    "svhn_policy = (parse_log_schedule('schedules/rsvhn_16_wrn.txt', 160), 'svhn_1000')\n",
    "\n",
    "def parse_policy_hyperparams(policy_hyperparams):\n",
    "    \"\"\"We have two sets of hparams for each operation, which we need to split up.\"\"\"\n",
    "    split = len(policy_hyperparams) // 2\n",
    "    policy = parse_policy(\n",
    "        policy_hyperparams[:split], augmentation_transforms_hp)\n",
    "    policy.extend(parse_policy(\n",
    "        policy_hyperparams[split:], augmentation_transforms_hp))\n",
    "    return policy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### User input possible in cell below\n",
    "\n",
    "Defaults to CIFAR policy and image of bird from CIFAR-10, at the final epoch of the schedule.\n",
    "\n",
    "You can change the image path (`image_path`), augmentation schedule (`cifar_policy` or `svhn_policy`), and which epoch to use within the schedule."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_size = 32\n",
    "image_path = 'figs/bird5.png'\n",
    "\n",
    "# Choice of either cifar_policy or svhn_policy\n",
    "policy, dset = cifar_policy\n",
    "\n",
    "# Epoch number to use for policy. 200 epochs for CIFAR and 160 for SVHN.\n",
    "epoch = 200\n",
    "\n",
    "# Number of images to display\n",
    "num_images = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Showing 10 example images at epoch 200.\n",
      "\n",
      "Applied augmentations:\n",
      "('TranslateY', 0.6, 7)\n",
      "('Contrast', 1.0, 7)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('Contrast', 1.0, 7)\n",
      "('TranslateY', 1.0, 0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('TranslateX', 0.8, 6)\n",
      "('TranslateX', 0.6, 6)\n"
     ]
    },
    {
     "data": {
      "image/png": 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sK3CXYH6Fv3amngjXlq3XeeJUO+LCYEyr/UKIfY7EL0SiSPxCJIrEL0SiSPxCJIrEL0SibGa7rmMA/hzdjAYHcNrdv2hmowC+AeA4ult2fdjdr8ceq95yvHwlnATTimwZ1emE6755myfhALyuWyVfpLG8z/OHdGIBOU/eaUdq+DWd17NrGH9qrMLPLUcSalo5bqM12H5oAHLlQRob6eO1BIHwnFT7+DjKkfOyMq8zePUCtyMvTF8Lts/MhdsBYKifj+MIz6nad2zmyt8C8AfufjeAdwP4fTO7G8ADAB519xMAHu39LYTYJ2wofnefdvcne7cXAZwBcATAfQAe6t3tIQAf3K1BCiF2nrf0nd/MjgN4J4DHAYy7+3QvdBk3U6KzEAmwafGbWT+AbwL4pLsvrI+5u6O7HhDqd8rMpsxsqhH72aQQIlM2JX4zK6Ir/K+6+7d6zTNmNtGLTwCYDfV199PuPunuk6VybIFOCJElG4rfzAzAVwCccffPrws9AuD+3u37AXxn54cnhNgtNpPV9ysAPgbgOTN7utf2KQCfBfCwmX0cwCsAPrzRAzXbHcxeC3/0L+e5BVSqhLPpPGLZIZKdt8SKAgJorzVorEBifUVu9ZEdvrpEtq6qr/FswGYzMv5W2DJdXOIu7ALpAwBDNW57VYeGaaxQCM9/qRyp01fkmXuX53gG4csv83p8t9xyLNheGeCeXc75Vm83ExuK393/EXyDsvfv7HCEEFmhX/gJkSgSvxCJIvELkSgSvxCJIvELkSiZFvD0dhPNpXAG1o0VXlCxUAzbTXmSwQYAxUhWnLe5jba2wi2xYjtsUw5XuFXWX+F2Xq6PW3b1Fb7d2JWZ4O+pAABDZFuu6jL/gVWlwmPtyNZm+UjBzU4nbJeVIpl79To/56eeeoHGLrx6kcby+bBRlc9xK7jdTuOamMZZCiF+BolfiESR+IVIFIlfiESR+IVIFIlfiETJ1OorWBsj+XB2VmONF2GsVMIZWPPz3EZrR05tdekqjdXX+P5/feWwjdZZ4ll9a5GsuEYkg9BbdRorRjIFlxbCBUjHxnghzokj4cw3AHDj9tvZcxdorL8Wtg8HB0Yjx+LXotVVXgim0+KWaaMensd2rGCscxvwZkJXfiESReIXIlEkfiESReIXIlEkfiESJdPV/lLecGw4nAxy5/gdtN/lpfCq+NoiT3CpVXg9uLcd7aexcpXXpWs2wivH9WWeKNQgW40BQDtc7bzbr8Fjs1d4PbtWK5xQUyOr7wBw5sxPaezylQUaq5DaigDwm+/7L8H2Uon3mb58icYGB3m/WvUIjc3OTAfb2+AOQbXMXzvcg9l/6MovRKJI/EIkisQvRKJI/EIkisQvRKJI/EIkyoZWn5kdA/Dn6G7B7QBOu/sXzewzAH4HwFzvrp9y9+/GHqtSLuLtt00EY8WIvTK2FE7quOvYIdqnTWrIAUAz8p73kxdforE7jhwIth8bH6J9ri0s0lhsV6g2sewAoN3hT9sA2UKr3uTW4eoyT2aqlvhcHTrEt7xaWAyf99oaN8titQkHSG1CAKj18fnIIfzaGR/hr7dapDbheV5qct+xGZ+/BeAP3P1JMxsA8EMz+34v9gV3/5PdG54QYrfYzF590wCme7cXzewMAP6rCiHEvuAtfec3s+MA3gng8V7TJ8zsWTN70MxGdnhsQohdZNPiN7N+AN8E8El3XwDwJQB3ADiJ7ieDz5F+p8xsysymVlZ58QohRLZsSvxmVkRX+F91928BgLvPuHvb3TsAvgzgnlBfdz/t7pPuPtlX5QspQohs2VD8ZmYAvgLgjLt/fl37+mX7DwF4fueHJ4TYLTaz2v8rAD4G4Dkze7rX9ikAHzWzk+jaf+cB/O5GD1QsFXGE2HNTTz5H++WK4Yy0ocgniflFvu3WasT2WlvhWWyN1Vqw/dhhnpE4dmCAxm5c5WM08GzA4QNhuxQAPBeek9VVfl7D/dxGK1fD5wwAL750jo9jLVxLcKDGH28tUqfv2jS3TIdH+GOW2fFy/Lp3/gLf/gsHTvDYPmMzq/3/CCBU0TDq6Qshfr7RL/yESBSJX4hEkfiFSBSJX4hEkfiFSJRMC3gCho4Vg5GRAzxDb/RgOJXglZfP0j6FIrevxqp8O6b8cW6jVcphG21hkRfwrEe2hbo4za2+Eye4pfS247fR2PUb4eKeA1X+Pl+IXALW+E5kuGUiss1Xm/yak1iR3Rg/WKvD7dn+Ab4V2cjBw8H2Z378Ch9HLZy9CdxcV8ub6VyEEG8BiV+IRJH4hUgUiV+IRJH4hUgUiV+IRMnU6uu0HWtLYetr/ACvDJavhosEDd/C7bC+HC8UWY5YSqOrvEKjIVxUs97kxTZfefU1GpvnSWyo5/l+gmvOM/5YwuLV2Rnap1wM268AkC/z4qQt40Uwq8MHg+2VKt8zsMTsQQB9g3wPxSMTozRWrIbHWOvjmYBDxFoGgMtXbp4KnrryC5EoEr8QiSLxC5EoEr8QiSLxC5EoEr8QiZKp1WfoINcJWyVLSzwzbolkqi01I9l53IXC6hovZlmr9dHYIsneW17h9k+JZAICwNED3KKqFCNPTZPP1er8lWD73NWrtE+hwO23tQ73I1+b4/N4YJTYs0PcYqv18bmyFj/nixf4/B86FJ7jo4fDViQAzF3ncwVEXlj7DF35hUgUiV+IRJH4hUgUiV+IRJH4hUiUDVf7zawC4DEA5d79/8rdP21mtwH4OoADAH4I4GPuHt2Gt1DIYfxAeGV5cWGW9lu+Hl7NXVnhCTULDb4CnLcmjd15O6+PNzIU3nprcZFvJZXL8ykeqvBYxXhiUr7Fj1fOhZ+C0VGeoLMWmUfv8Nj1OZ60dO3y+WD74DB3OKoVvto/PsRX2RtlPsZyIZzptNTgTtHMa5f54x1+B43tNzZz5a8DeJ+7vwPd7bjvNbN3A/gjAF9w9zsBXAfw8d0bphBip9lQ/N5lqfdnsffPAbwPwF/12h8C8MFdGaEQYlfY1Hd+M8v3duidBfB9AC8BuOHuryfGXwTAk6CFED93bEr87t5295MAjgK4B8DbN3sAMztlZlNmNrW4HKleIYTIlLe02u/uNwD8PYD/BGDYzF5fsToK4BLpc9rdJ919cqDGf0YqhMiWDcVvZgfNbLh3uwrg1wGcQfdN4L/17nY/gO/s1iCFEDvPZhJ7JgA8ZGZ5dN8sHnb3vzazHwH4upn9IYCnAHxlowfKWw61StiyGYtYQBdfCydaVAu8ll2hxrdwqje4jdZochuw1Q5bbKVIDbzrNyI2YIfXEmzW52nswNBxGqtWw3bZYJsfK9fkDu1IHz+3I4d4ncHFpbDVem0+nKQFAPUGT/o5VOPjaOb4lmj1Zvi5LhUjtQSN24A3ExuK392fBfDOQPs5dL//CyH2IfqFnxCJIvELkSgSvxCJIvELkSgSvxCJYu5kf6fdOJjZHIBXen+OAQgXnMsWjeONaBxvZL+N41Z35wUK15Gp+N9wYLMpd5/ck4NrHBqHxqGP/UKkisQvRKLspfhP7+Gx16NxvBGN443ctOPYs+/8Qoi9RR/7hUiUPRG/md1rZj8xs7Nm9sBejKE3jvNm9pyZPW1mUxke90EzmzWz59e1jZrZ983sp73/w/td7f44PmNml3pz8rSZfSCDcRwzs783sx+Z2Qtm9t977ZnOSWQcmc6JmVXM7Adm9kxvHP+7136bmT3e0803zIxXPN0M7p7pPwB5dMuA3Q6gBOAZAHdnPY7eWM4DGNuD4/4qgHcBeH5d2x8DeKB3+wEAf7RH4/gMgP+R8XxMAHhX7/YAgBcB3J31nETGkemcADAA/b3bRQCPA3g3gIcBfKTX/n8B/N52jrMXV/57AJx193PeLfX9dQD37cE49gx3fwzAtTc134duIVQgo4KoZByZ4+7T7v5k7/YiusVijiDjOYmMI1O8y64Xzd0L8R8BcGHd33tZ/NMBfM/Mfmhmp/ZoDK8z7u7TvduXAYzv4Vg+YWbP9r4W7PrXj/WY2XF060c8jj2ckzeNA8h4TrIompv6gt973P1dAH4LwO+b2a/u9YCA7js/um9Me8GXANyB7h4N0wA+l9WBzawfwDcBfNLd37D/d5ZzEhhH5nPi2yiau1n2QvyXABxb9zct/rnbuPul3v+zAL6Nva1MNGNmEwDQ+59vYbSLuPtM74XXAfBlZDQnZlZEV3Bfdfdv9Zozn5PQOPZqTnrHfstFczfLXoj/CQAneiuXJQAfAfBI1oMws5qZDbx+G8BvAHg+3mtXeQTdQqjAHhZEfV1sPT6EDObEzAzdGpBn3P3z60KZzgkbR9ZzklnR3KxWMN+0mvkBdFdSXwLwP/doDLej6zQ8A+CFLMcB4Gvofnxsovvd7ePo7nn4KICfAvg7AKN7NI7/B+A5AM+iK76JDMbxHnQ/0j8L4Onevw9kPSeRcWQ6JwD+PbpFcZ9F943mf617zf4AwFkAfwmgvJ3j6Bd+QiRK6gt+QiSLxC9Eokj8QiSKxC9Eokj8QiSKxC9Eokj8QiSKxC9Eovwr6+n9zXAuOz8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('Solarize', 1.0, 5)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('Equalize', 1.0, 6)\n"
     ]
    },
    {
     "data": {
      "image/png": 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+EOKtxbzO7+5PA+CpToUQb0sW8pv/bjPba2YPmFlUZmUhxFuQ83X+rwJYD2ALgF4AX2RvNLPtZrbLzHZNTfLfMEKI6nJezu/up9294O5FAF8DsC3ivTvcfau7b61v4AszQojqcl7Ob2bnLqHeDuDlCzMcIUS1qETq+zaAmwF0mNlJAJ8FcLOZbQHgALoBfLKivRmQTIXLCZ0eiZDtSIK/VIHLGuuauA5V28JLV00N8Si2mXxYyolIL4d8jh/XKInmAoCxcW5L53l+wjqEZaMa46c6P8slqmyRS2zZw3yuMoPh465bziPmUg08qi8/HhFteWMbt3WE8wIWnd/3Rnr3UNvYQT4fP+rm8zE8zW2rusJLZitr+HXaWR+W+v4hE6G/zmFe53f3jwWa7694D0KItyR6wk+ImCLnFyKmyPmFiClyfiFiipxfiJhS1QSeyzpq8elPXBa0jb/UQ/uRal14oZdHSo1GJJ5csfEd1DZ+Yhe1ZbOTwfaE8USLyQjb4YOv8X45nqRz8ypeMmp9c3OwPZEMjx0AGjp5+S8+i8DBY8eorT0flvQyUWF9zVxGq7ucRyWmW3ixt3wxPI9n/ul7tM+RZ09TW3sXj4DsG+MRoUOT49TWQ8qNNdXwY75hdTgBaQ1UrksIMQ9yfiFiipxfiJgi5xcipsj5hYgpcn4hYkpVpb6Z8RkceurVoG02yyP09g+H2395dCBsADA6xBOHzGZ5pF26dgm11ebDCTyLEclCCzkejTY+zeW3jqU8Um356rBcCgDvXBe2Na3mcpjxYDr4NB//5a1rqC3TGZbEkpt4VJ9FZAS1NL9PJSIiFsdOHQ22//q34XYAODXIE7KO9XLxc2SCS3NTI1wWLZDakaPg5+x74+HzPDwTUYdyDrrzCxFT5PxCxBQ5vxAxRc4vREyR8wsRU6q62t89MIk//bvfBG2JAl9FHT8dDnzIT/BaWPlpHhiTrIk47AIPxEmnwyvVBeMBHbkpHtDh6Rpqa+xYS22b1l5JbQ03LQu21629lPZJJfhyfzbLV8UL/eHSawBgteHzmVjC5z6ZCOelAwAzvvKdLfBglk//h58G20fGePBOfoKfs+FJfl0NDPLroKWVKwHXX3V1sH3vqydonymEVakoJWsuuvMLEVPk/ELEFDm/EDFFzi9ETJHzCxFT5PxCxJRKynWtAvANAF0olefa4e5fMbM2AA8DWINSya473J2E4JTIzxYx0B2WIgqzXKIoFsIyj+d58EtpuGFqkjx4x1KH+CZpXj1er8sjPl+LEdM/meTyW6qBjz/RGe5XJNIQABQ8IqAmwQNxapZHFV4NBzslkhEBRgl+zgCed7GYfZLadr8UPp9nTnXTPnVN4TyIAFCb4oFOBXDp9tQgD1w7QHJR1jbxa6C+ISyLJhLhcnjB91bwnjyAT7v7ZgDXA/iUmW0GcC+Ap9x9I4Cnyn8LId4mzOv87t7r7rvLr8cB7AewEsBtAB4sv+1BAB+8WIMUQlx43tRvfjNbA+AaAM8A6HL33rKpD1Hfs4UQbzkqdn4zawTwfQD3uPvrMmW4uwPhhOFmtt3MdpnZLi/wxx+FENWlIuc3szRKjv+Quz9abj5tZsvL9uUA+kN93X2Hu291960WsYglhKgu8zq/mRmA+wHsd/cvnWN6DMBd5dd3AfjhhR+eEOJiUUlU37sA3AngJTPbU277DID7ADxiZh8HcAzAHfNtqJgvYHJgKGizJJeNUrXhfHCe4rJRVHTe9NQUtRVn+U+TZD5sq0nyHH5JPgwAPIpteiw8TwAwMMP3V5wOS0r5Wh4hlitwGSqd4lJfIsWjC82YfMhltKj5yBV5Xr1jj/IIvauuelew/cgyLh2mily67WjkOfKGRnm/gUkuESIZnpPaWu6eQ6ePB9vz+cqj+uZ1fnf/NQAmHr634j0JId5S6Ak/IWKKnF+ImCLnFyKmyPmFiClyfiFiSlUTeHpxCoWZPUFbMcelrWwqHL2XsIiovgSPsEKRJ2Es5rr5Jj0s8xRSXCqrTXOtr7aGyz8zY7wU2d5X91Hb8R+Ej7t1NZfs6jdxybTYxROrJpLd1ObOovpW0j6sbBUA/OIvf0ttD73wCrWlMuH5Tyf4ecnxQ0YxE5adASCd5NdVSwN3tcHecCLaFZ38nA32ha+PfI7LjXPRnV+ImCLnFyKmyPmFiClyfiFiipxfiJgi5xciplRV6ktYDjXJcHTWzMxYsB0AEqlwgsNclkeqJSKSKRYLUXlGuWxXJJ+VHlFnsJDlU5zP8Qgsj5C99uymJvxFT7i23sbLVtM+//qdW6ktFxE5eWD0GLXdsCpcm67jij7ax9P8XvTy+CS1zc7wKM3xsXA9wdwUn998kcuAnUs38n2lW6htcJDPVR+xpQpcVpwcC9evLBYk9Qkh5kHOL0RMkfMLEVPk/ELEFDm/EDHFSlm3q0MmnfZl7R1BW6qOryqPTYRz542cGaR9Emm+yl6f4bni0hH98rnwCnE+x3Pq5Z2XT4qqrFQXFRBUy8tr1bd1BtuvuZrnrBuf5ivERw7z1fm6Jr4a/ePPfzLc5xreZ9/DPE9fQ31EabMxPv5HDoeDfl47yRWCjiYeMNbcwcfR28+32dLCz9nLz/4i2D42eJD2qW8KKwv7X+vD5FS2oppduvMLEVPk/ELEFDm/EDFFzi9ETJHzCxFT5PxCxJR5A3vMbBWAb6BUgtsB7HD3r5jZ5wB8AsDZZGKfcffHo7ZVX1+HLdeGSzzVNS6l/Y6dDgcxzGZ5aa18RAmqHLiMdmr/M9TWuWJ5sP3yDZfQPid6e6mtGJErrjDLx19wHrTUsjQcwDM+zSXdsUGeL7Chgc/VhsveSW0nXgsHajUP8ryFjx4+Qm2bW3k5t21NXEZLIZwb8rp1YckZADbVcTnyu7v/idryxuXqzqZV1Fb0cIBXWwsf42yx8rJcjEqi+vIAPu3uu81sCYDnzezJsu3L7v4/FjwKIUTVqaRWXy+A3vLrcTPbD4CnYBVCvC14U7/5zWwNgGsAnP1ufLeZ7TWzB8ys9QKPTQhxEanY+c2sEcD3Adzj7mMAvgpgPYAtKH0z+CLpt93MdpnZrmyWPwYrhKguFTm/maVRcvyH3P1RAHD30+5ecPcigK8B2Bbq6+473H2ru2/NRDxTL4SoLvM6v5kZgPsB7Hf3L53Tfu7S9+0AXr7wwxNCXCwqWe1/F4A7AbxkZmdrbX0GwMfMbAtK8l83gHAY1zksaajHu7deE7Td/8hDtJ/VNAfbOxu4JNMfkV9uNkJGy0X8NCmMh3MJvv+qK2ifno1cBjx4kEtbCfBvSZs2/h61FVLhORkYCpeEAoA1XTz3XHvbMmp7/OdPUNsXRg8H21d3rqB9hobDki4A/J8XeHTh3jXt1NbaRdamk/zS/+6uX1HbNE/9h85V/Nie+e3T1DY2Es4zeMkynndxZpbJs5Uv41Wy2v9rAKEQwUhNXwjx1kZP+AkRU+T8QsQUOb8QMUXOL0RMkfMLEVOqWq7LkUA2ES7j1HUpTzC59rJ3Bduf+xUXHNKZ8H4AoKOBf+ZFfRrW1tUF2w+c4lFxExHa0IFXuRx5401/TG1/dtPV1PabV8NyWW4JP9WdEQf9asRDmVdeeSM3Zkn5tdQS3ifFE2BmczwEct2KtdR2y4bwdXXPT3bycXTwaMWPbQtL1QAQEVyI+w6/Rm1T48eD7fuH9gTbAaC+LSzPRkWzzkV3fiFiipxfiJgi5xcipsj5hYgpcn4hYoqcX4iYUlWpL5d3DJAEjlesD8t5AFDTHI4sW3HVB2ifljSRmgA0p7j8Njh0mtoSCOteE9NcD3v+BS7XTExSE0YzPJpurMCTavaTPJ27X9tN+7REJKysabqU2qYTPHlT+6Ubgu1LG7gE27ws3AcAulaup7aPXMOzyqVWNATbO5/ron02rOFS35YVPEnnzmNcqlxz9e9TW0fXpmD7YVJnEADSqfA1lzjNr/s3vLfidwohfqeQ8wsRU+T8QsQUOb8QMUXOL0RMkfMLEVOqKvWZ55HOh6POevp4ZNzAsaPB9qEpLnkl2/g4RkfD2wOAzqVcAuo9FZYBj46G68EBQKY+HAkIAKsu4fJVaz2XlDDGJaWe/nBS0IOHD9E+mTRP4DlOzhcAnD7Jk2o2LQ9LhF0reJLLtg4uOSZn+Bx/c+cgtX1obXiO79q4jvb54elT1PYtPgyMTPHIw0JErcT2jrBk6slraZ+W9nC9xr6TPFJ0LrrzCxFT5PxCxBQ5vxAxRc4vREyR8wsRU+Zd7TezWgBPA6gpv/977v5ZM1sL4DsA2gE8D+BOd89Gbas9k8Sdq8Mry/+tZy/tN3wyrARMjvF8ZQcOhEsgAUDCeCBO+9ZgvVEAwKWrwqW3BgZ6aZ9khq/2dzXzIJelCR6gkZng22xLjQfb16zlwS/DQ3lq8yy3HT1zgNomBvcF20eOcmUhXcuPq7ODl+SaOsLHeGlNeAX+pUl+39u7iwdBbdp8JbV1tnH1pr+fKwjHj4dVk2KSn7NJUo4uOxtRT2wOldz5ZwG8x92vRqkc9y1mdj2ALwD4srtvADAM4OMV71UIsejM6/xe4myFynT5nwN4D4DvldsfBPDBizJCIcRFoaLf/GaWLFfo7QfwJIDDAEbc/ez3rZMA+HcUIcRbjoqc390L7r4FwCUAtgHgSfbnYGbbzWyXme0anpw+z2EKIS40b2q1391HAPwcwA0AWszs7ILhJQB6SJ8d7r7V3be2NvAFHSFEdZnX+c1sqZm1lF/XAXg/gP0ofQh8uPy2uwD88GINUghx4akksGc5gAfNLInSh8Uj7v4PZvYKgO+Y2X8B8AKA++fdWTKFjiVhqeeqSzfSfnv3h4NS6jK8PlKmmQfoTM9MUNv4bDjHIABMD50MttfW8oCUwQEe/HKiwH8GzUycoLbbO95DbZuXhMthjS7lwUDpSS4rLlnJj+3EEV56a3Y8vL+JyVHaJ5Pnc+9LuCw6k+IK87HpcCROe30H7dOQ5PfE1155idpalkdcO4Pd1FZaQ38jfad4FFHCwucsn+VjmMu8zu/uewG8oUCZux9B6fe/EOJtiJ7wEyKmyPmFiClyfiFiipxfiJgi5xcippg7zy12wXdmNgDgbDhSBwCefK16aByvR+N4PW+3cVzq7ksr2WBVnf91Ozbb5e5bF2XnGofGoXHoa78QcUXOL0RMWUzn37GI+z4XjeP1aByv53d2HIv2m18Isbjoa78QMWVRnN/MbjGzV83skJnduxhjKI+j28xeMrM9Zrarivt9wMz6zezlc9razOxJMztY/j9cw+nij+NzZtZTnpM9ZnZrFcaxysx+bmavmNk+M/vzcntV5yRiHFWdEzOrNbNnzezF8jg+X25fa2bPlP3mYTPjYa2V4O5V/QcgiVIasHUAMgBeBLC52uMoj6UbQMci7PcmANcCePmctv8O4N7y63sBfGGRxvE5AH9R5flYDuDa8uslAF4DsLnacxIxjqrOCQAD0Fh+nQbwDIDrATwC4KPl9r8F8G8Wsp/FuPNvA3DI3Y94KdX3dwDctgjjWDTc/WkAc4O1b0MpESpQpYSoZBxVx9173X13+fU4SsliVqLKcxIxjqriJS560tzFcP6VAM7NVLGYyT8dwBNm9ryZbV+kMZyly93PFgDoA8CzkVx87jazveWfBRf958e5mNkalPJHPINFnJM54wCqPCfVSJob9wW/G939WgB/DOBTZnbTYg8IKH3yo/TBtBh8FcB6lGo09AL4YrV2bGaNAL4P4B53f12qmmrOSWAcVZ8TX0DS3EpZDOfvAbDqnL9p8s+Ljbv3lP/vB/ADLG5motNmthwAyv/3L8Yg3P10+cIrAvgaqjQnZpZGyeEecvdHy81Vn5PQOBZrTsr7ftNJcytlMZz/OQAbyyuXGQAfBfBYtQdhZg1mtuTsawB/BODl6F4XlcdQSoQKLGJC1LPOVuZ2VGFOzMxQygG5392/dI6pqnPCxlHtOala0txqrWDOWc28FaWV1MMA/v0ijWEdSkrDiwD2VXMcAL6N0tfHHEq/3T6OUs3DpwAcBPB/AbQt0jj+N4CXAOxFyfmWV2EcN6L0lX4vgD3lf7dWe04ixlHVOQFwFUpJcfei9EHzH8+8gOtUAAAAQElEQVS5Zp8FcAjAdwHULGQ/esJPiJgS9wU/IWKLnF+ImCLnFyKmyPmFiClyfiFiipxfiJgi5xcipsj5hYgp/w+C6mSovVrjQgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('Color', 0.9, 4)\n",
      "('Cutout', 0.5, 2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('AutoContrast', 1.0, 9)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('AutoContrast', 1.0, 9)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n",
      "('AutoContrast', 1.0, 9)\n",
      "('Contrast', 1.0, 7)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applied augmentations:\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load image\n",
    "img = np.array(PIL.Image.open(image_path))\n",
    "\n",
    "# Normalize Image\n",
    "img = img / 255.\n",
    "img = (img - augmentation_transforms_hp.MEANS[dset]) / augmentation_transforms_hp.STDS[dset]\n",
    "\n",
    "print('Showing 10 example images at epoch {}.\\n'.format(epoch))\n",
    "\n",
    "for _ in range(num_images):\n",
    "    # Apply augmentations\n",
    "    print('Applied augmentations:')\n",
    "    img_aug = augmentation_transforms_hp.apply_policy(\n",
    "        policy=parse_policy_hyperparams(policy[epoch - 1]),\n",
    "        img=img,\n",
    "        aug_policy='cifar10',\n",
    "        dset=dset,\n",
    "        image_size=image_size,\n",
    "        verbose=True)\n",
    "    \n",
    "    # Unnormalize Image\n",
    "    img_aug = (img_aug * augmentation_transforms_hp.STDS[dset]) + augmentation_transforms_hp.MEANS[dset]\n",
    "    \n",
    "    plt.imshow(img_aug)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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